How can you forecast revenue for a SaaS company?

Defining assumptions is foundational when forecasting revenue for a SaaS company. Understanding the variables that impact revenue is paramount. Drawing from historical data, industry benchmarks, and well-informed projections is vital. What adds depth to the process is scenario testing.

First of all, it is important to understand different characteristics between B2B and B2C SaaS companies when forecasting revenue. In my experience, revenue forecasting for B2B SaaS company should be fairly granular. Certain common variables like Total Addressable Market shall only be used in strategy process, not in revenue forecast which feeds cash forecast and thus is crucial for financing operations. Key SaaS B2B revenue forecast assumptions are 1) existing customer revenue run rate 2) revenue ramp-up from signed deals (if any ramp-up) 3) price increases 4) churn rate assumption (historic) 5) new bookings assumption, including phasing and revenue ramp-up 6) implementation project revenue recognition forecast (if any)

I agree that number customer x average revenue can be useful approach for many companies, but it won’t give accurate results in B2B environment where deal sizes and new customer acquisition volumes varies a lot. First of all, existing customer montly revenue can be recieved from invoicing system. Secondly sales leadership (with help of CRM) can feed approximation for new customer bookings, which can be used for new customer revenue forecast.

Calculating Monthly Recurring Revenue (MRR) is pivotal in revenue forecasting for SaaS companies. MRR, derived from existing customers, is a reliable revenue stream. Accurate MRR calculations are essential for gauging financial stability and optimizing growth strategies in the ever-evolving SaaS landscape.

Depending on industry and company pricing models, some companies can have revenue ramp-up period from bookings. This means annual year forecast should be calculated summing up months. Still ARR = MRR x 12 in given month

Calculating non-recurring revenue (NRR) in SaaS revenue forecasting is pivotal. NRR, stemming from various sources beyond subscription fees, is a key component. This holistic approach enables SaaS companies to make informed decisions and adapt their strategies in an ever-evolving market. It's a strategic necessity in SaaS revenue forecasting.

I'm trying to do this for a start-up I am working with. I don't have much historic data to go on so I am going to base it on the percentage of both additions and total users. The challenge will be finding a sensible assumption, currently looking for any comparative information I can use in the first instance.

The formula presented consolidates recurring and non-recurring revenue sources, offering a comprehensive outlook. Accurate total revenue calculations are pivotal in strategic planning, enabling SaaS companies to chart their financial course and make informed decisions to thrive in a dynamic market. It's the capstone of effective SaaS revenue forecasting.

Business model and the types of service offerings I begin by understanding the business model, then the types of services offered. We can start with Cloud Bookings for existing deals. Based on their offerings, companies can offer Metering or Non-metering deals. Non-metered offerings are relatively easy to forecast Revenue since the forecast is based on Bookings divided by the Service Period. Metered offerings, however, depend on consumption, so establishing a consumption pattern can be challenging. However, we can use historical data, inputs from the sales team, or even new Bookings data to indicate consumption rates for existing Bookings. And for Revenue Forecasting from new opportunities, the base can be forecasted Bookings.

Revenue forecasts are like weather predictions. Lots of complicated models exist, but the best prediction for tomorrow's weather does not require complex math. It is simply today's weather. Use the same principle to forecast revenue for your SaaS. Look at how MRR evolved for a similar period. That is usually the previous months, but if your business is seasonal find another comparable period. This will give you an expected growth rate.?? The next step is factoring in possible changes in this rate. Speak with your sales team to find out if there are any big deals in the pipeline. Do the same with the customer success team to see if any large clients are expected to churn. Update your prediction accordingly.

This formulaic approach, grounded in precise calculations, equips SaaS businesses with a clear and dynamic revenue projection.